Coherence Optimized Channel Estimation for Mm-Wave Massive MIMO

Abstract

Mm-wave MIMO communication makes a hybrid combination of analog RF and digital baseband processing more attractive, where digital baseband precoders/combiners able to adapt to the pre-defined analog (switch based) RF processors. Non-uniform two-dimensional quantized azimuth and elevation angle grid antenna array responses are suggested for uniform planar array (UPA) and are proven orthogonal. Training vectors (or sensing matrix) are designed for suggested antenna array response with unitary RF processing for UPA in mm-wave hybrid MIMO system. Proposed training vectors achieve minimized total coherence of the equivalent sensing matrix for hybrid MIMO system. Open-loop channel estimation of the mm-wave channel is done by using iterative re-weight based super resolution algorithm to exploit its sparse nature. Extensive simulations reveal the benefit of coherence optimization where normalized mean squared error is reduced and spectral efficiency is improved in comparison to existing methods.

Keywords

• channel estimation
• compressed sensing
• hybrid mimo
• mm-wave communication
• sparse channel